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Media & Information Literacy
Source evaluation, fact-checking, misinformation and deepfakes — judging what is true on any screen.
Source evaluation, fact-checking, deepfakes and statistical lies — a procedure for judging what is true on any screen. News Literacy Project, Stanford SHEG, Poynter and more: 43 resources (42 free).
Calling Bullshit: Data Reasoning in a Digital World
Carl Bergstrom and Jevin West's University of Washington course on spotting bullshit dressed as data: misleading graphs, percentages without bases, cherry-picked studies, and machine-learning hype. The full syllabus, lectures and case studies are free, with a reading list that doubles as a field guide. Aimed at students and citizens who must judge numbers daily. Free, and the best-known university course of its kind.
Checkology Virtual Classroom
The News Literacy Project's e-learning platform: interactive lessons and exercises where students evaluate sources, evidence, claims and news, with quizzes and a teacher dashboard. Its units cover what misinformation is, how to read laterally, and how to judge whether a claim deserves belief. Built for grades 5-12 classrooms and lifelong learners; free accounts for educators, with premium tiers. From the leading US news-literacy nonprofit.
Crash Course Navigating Digital Information
A ten-part Crash Course series produced with the Poynter MediaWise project, hosted by author John Green. It separates data, information, claims and opinions on every screen, then teaches fact-checking, source evaluation, evidence and Wikipedia reading as repeatable habits. Built for teens and adult beginners who want one fast, rigorous pass over judging online information. Free on the web and YouTube, with episode pages that double as lesson material.
Don't Take the Bait! - Common Sense Education
A Common Sense Education lesson on clickbait: how headlines are engineered to bypass judgment, why ads reward outrage and curiosity gaps, and how to notice the pull before clicking. Students examine real examples and practice rewriting bait into honest headlines. Built for K-12 classrooms and adaptable for adult learners. Free, with full lesson plans, videos and activities from the most-used digital-citizenship curriculum in the US.
Fact-Checking Fundamentals with IFCN
A free self-paced course from Poynter's International Fact-Checking Network covering fact-checking methodology, verification and debunking, and health mis- and disinformation. Three modules teach how to find fact-checkable claims, apply professional verification methods, and use the tools working fact-checkers rely on. Built for journalists, academics and aspiring fact-checkers; available in 15 languages with a certificate. Backed by the body that sets the global fact-checker code of principles.
Is This Legit? Digital Media Literacy 101 - Poynter MediaWise
MediaWise's free self-guided course in fact-checking basics: lateral reading, reverse image search, finding the original source, and recognizing misinformation red flags. Short lessons with real examples are drawn from the teen fact-checking network's daily work. Built for teens, educators and any adult who wants a verification routine. Free from Poynter's MediaWise, the US leader in digital media literacy.
Mindware: Critical Thinking for the Information Age
University of Michigan professor Richard Nisbett's course on thinking tools for an information-saturated world: cost-benefit reasoning, correlation and causation, statistical intuition, and the psychological biases that distort judgment. Short lectures with quizzes let you test each concept immediately. Aimed at adult learners and students who want the cognitive toolkit behind good judgment. Free to audit on Coursera.
Power Searching with Google
Google's official free course on getting better results: how the search engine interprets queries, operators and filters, and how to judge the results you get back. Short lessons with activities and a searchable archive let you practice each technique immediately. Designed for students, teachers and any adult who searches daily but never learned the mechanics. Free, self-paced, and taught by Google's own search education team.
Sorting Truth From Fiction: Civic Online Reasoning (MIT OpenCourseWare)
MIT OpenCourseWare's complete materials for Sorting Truth From Fiction, a course on civic online reasoning built from Stanford's research. You work through lessons and practice spaces that habituate verification before believing, signing or sharing - evaluating evidence, sources and claims with one consistent routine. Free for self-study or group teaching, with facilitation guides included. University-grade material from MIT's comparative media studies program.
Trust and verification in an age of misinformation
A free massive open online course from the University of Texas Knight Center teaching how to identify and verify what you see on the web in an age of misinformation. You learn practical verification workflows and tools used by working journalists - sourcing, reverse search, metadata and cross-referencing - applied to real examples. Self-paced for journalists, students and the general public. Produced by the Knight Center, which has trained journalists worldwide.
Wiki Education Student Training Modules
Wiki Education's free training modules for students editing Wikipedia: how articles are built, what sourcing and neutrality mean in practice, and how to read talk pages and edit histories as evidence. Interactive modules with exercises are used in hundreds of university courses. Perfect for learners who want to see how open knowledge is actually produced. Free from the nonprofit that runs Wikipedia classroom programs.
Civic Online Reasoning
Free research-based curriculum from Stanford's History Education Group (now the Digital Inquiry Group) teaching civic online reasoning: lateral reading, source checking, and evidence-based judgments about online content. Its lessons give a repeatable verification checklist - leave the page, find who is behind the claim, corroborate before you trust or share. Designed for classrooms but fully usable for self-study. Grounded in studies of how professional fact-checkers actually verify.
Civic Online Reasoning Curriculum
The Stanford History Education Group's Civic Online Reasoning curriculum: free, research-validated lessons in lateral reading, author and evidence evaluation, and primary versus secondary source judgment. Students practice on real viral content with assessments that measured dramatic skill gains. Built for classrooms and self-learners who want source evaluation as a procedure, not a slogan. Free from the Digital Inquiry Group, the most-cited research team in online reasoning.
A Beginner's Guide to Social Media Verification - Bellingcat
Bellingcat's beginner walkthrough of verifying social media content: how to check an account's history, read a photo for clues, and run the independent checks before believing or sharing viral media. Concrete, screenshot-heavy and written to be followed step by step. Aimed at first-time fact-checkers and curious sharers. Free from the investigative group that set the public standard for open-source verification.
AI and Information Literacy - UC Irvine Libraries
A university library research guide to evaluating what generative AI produces: where chatbots and AI search summaries get things wrong, how to check their claims against sources, and how to cite or avoid them honestly. It frames AI output as something to verify like any other source rather than trust by default. Built for students and researchers working in the 2026 reality of AI-written answers. Free, published by UC Irvine's subject librarians.
AI Detection Tips for Fact-Checkers
A free tipsheet from WITNESS compiling effective practices from journalists and fact-checkers for detecting AI-generated audiovisual content. You learn what detection tools can and cannot confirm, how to combine them with contextual checks, and how to respond when synthetic media is suspected. Drawn from Deepfakes Rapid Response Force partners' real casework with at-risk communities. Published by WITNESS, the human-rights organization leading synthetic-media preparedness.
Evaluating Information: Generative AI - University of Washington Libraries
UW Libraries' evaluation guide extension for generative AI: a compact method for judging AI-written summaries, snippets and chat answers, including what these systems can't know and how confidently they fabricate. It pairs the classic source-evaluation checklist with AI-specific failure modes. Written for students and researchers but directly usable by anyone reading AI search answers. Free from one of the strongest research-library teaching programs.
Guide to Using Reverse Image Search for Investigations
Bellingcat's practical guide to reverse image search for investigations - the open-source research group's field method for tracing where an image came from and whether it was reused out of context. You learn to run Google, Yandex and TinEye searches, crop and re-scan strategically, and read exactly what results do and do not prove. Aimed at journalists, researchers and anyone verifying images in their feed. Published by the investigations outfit famous for tracing conflicts with open sources.
Making Sense of Statistics - Sense About Science
Sense About Science's free guide to interrogating statistical claims: what a study actually measured, whether a base rate is given, relative versus absolute risk, and the questions to ask when someone says 'studies show'. Written in plain language with real media examples. Built for non-scientists: journalists, students, patients, citizens. Free PDF from the UK nonprofit that pioneered public statistical literacy.
People + AI Guidebook
Google's People + AI Guidebook: a research-based set of patterns for designing and using AI systems with humans firmly in the loop. Its chapters on mental models, trust, feedback and human-AI collaboration teach why probabilistic output demands deterministic checking - and how to keep judgment with the person. Written for designers, builders and working users alike, with concrete dos and don'ts. Produced by Google's PAIR research initiative from real product experience.
Verification Handbook
The Verification Handbook series from the European Journalism Centre: the standard free reference for verifying user-generated photos, videos and claims, now covering AI-generated and manipulated media. Chapters are written by working verifiers and walk the actual procedures: reverse image search, geolocation, provenance and cross-checks. Built for journalists and fact-checkers but the procedure is exactly what citizens need. Free ebooks and case studies.
Verifying Online Information: The Absolute Essentials - First Draft
First Draft's essential verification guide: the core procedure for checking images, videos and claims before sharing - provenance, reverse search, corroboration, and knowing when evidence runs out. Written by the training team that taught verification to newsrooms worldwide. For journalists, students and citizens alike. Free, and the shortest complete statement of the verification habit the course teaches.
AI Risk Management Framework (AI RMF 1.0)
NIST's AI Risk Management Framework - the US standard for reasoning about AI risk by context and severity, organized around govern, map, measure and manage functions. You learn to grade situations by stakes, which is exactly the risk-tier thinking that decides where human verification is mandatory versus optional. Free playbooks and crosswalks make the framework usable outside large organizations. Developed with hundreds of industry and civil-society participants.
Authorship and AI tools (COPE position)
COPE's position statement on AI tools and authorship: AI tools cannot meet authorship criteria, authors must declare AI use, and accountability for the work stays entirely human. It frames the practical rule that governs who owns and who answers for AI-assisted output across thousands of journals. Essential studied material for understanding attribution and responsibility in generated work. Issued by the global body that sets publication-ethics standards.
Bellingcat Online Investigation Toolkit
Bellingcat's collaborative open-source investigation toolkit: the maintained index of techniques, tools and guides for verifying images, tracing sources and geolocating content, with handbooks on everything from satellite imagery to social media profiles. It is the working desk reference of the world's best-known citizen-investigation team. For investigators, journalists and learners building real verification skill. Free, community-maintained.
Copyright and Artificial Intelligence (U.S. Copyright Office)
The U.S. Copyright Office's official hub for copyright and AI, including registration guidance for works containing AI-generated material and its multi-part report on digital replicas and copyrightability. You learn the operative rule today: purely generated content is not copyrightable, human authorship and selection can be, and disclosure matters. The authoritative source behind evolving case law, free to read. The agency's statements are what registries and courts actually follow.
Ethics and governance of artificial intelligence for health
The WHO's guidance on ethics and governance of AI for health, covering the principles that should govern AI in medicine and the specific risks of unverified outputs in clinical contexts. It shows what the highest risk tier demands: accuracy, accountability and human oversight wherever harm is real. Free to read, aimed at policymakers, developers and health professionals. Issued by the World Health Organization after multi-year expert consultation.
Google Search Central: How Search Works
Google's official in-depth guide to how Search works: crawling, indexing, and ranking, plus how paid and organic results are separated and ordered. The clearest primary-source explanation of what happens after you press enter on a query. Aimed at site owners, students, and anyone curious about search. Free documentation from Google Search Central.
How Google Search Works: Ranking Results
Google's own explainer on how Search decides what to rank: crawling, indexing, hundreds of ranking signals, and how relevance and quality are weighed. Reading it shows why two people can query the same words and get different results. Written for curious searchers, students and teachers who want the mechanism behind the results page. Free official documentation, the primary source for how the dominant search engine actually works.
Use of AI by Authors (ICMJE Recommendations)
The International Committee of Medical Journal Editors' binding guidance on using AI-assisted technology in scholarly work: AI tools cannot be listed as authors, and their use must be documented in the manuscript. You learn the disclosure standard the world's top medical journals enforce - attribution, transparency, and human accountability for every claim. A short, authoritative reference for research and professional writing. Maintained by the body that sets global medical-journal standards.
Journalism, 'Fake News' and Disinformation - UNESCO Handbook
UNESCO's open-access handbook for journalism education that maps the whole information-disorder landscape: misinformation versus disinformation versus mal-information, how false claims are made and travel, and how to verify and debunk. Chapters come with exercises and teaching notes used in classrooms worldwide. Written for journalism students, educators and anyone who wants the rigorous definitions behind the buzzwords. Free PDF from the UN's media-literacy lead agency.
Web Literacy for Student Fact-Checkers
Mike Caulfield's open textbook on checking the web like a fact-checker: the SIFT method - stop, investigate the source, find better coverage, trace claims - practiced on live examples. Each chapter is a set of moves you perform in your browser, not rules you memorize. Built for students and self-learners who want the habit of pausing before sharing. Free online, the canonical source of lateral-reading pedagogy.
Crash Course Media Literacy
Crash Course's twelve-episode media literacy series: how media industries make money, how advertising and attention economics shape what you see, and how persuasion is engineered across platforms. Each episode is a fast, densely researched explainer with references. Aimed at students and adults who want the structural view of why feeds behave the way they do. Free on YouTube from the most-watched education channel in the genre.
Beware Online Filter Bubbles - Eli Pariser (TED-Ed)
The TED talk that named the filter bubble, delivered by the author who coined the term. Pariser shows how personalization quietly curates what each person sees, narrowing the shared information picture without anyone opting in. Aimed at general audiences and classrooms; the TED-Ed page adds discussion prompts for study. Free to watch, one of the most-cited explanations of why your results differ from everyone else's.
AI Awareness Training (Which One Is Real)
A free, self-paced AI literacy course (10 chapters, 30-35 minutes, no account) devoted to verifying AI-generated images before you trust, share or act on them. It opens with a no-hints test showing how unrecognizable synthetic images have become, then teaches the checks that hold up: context, reverse image search, detector signals, and source confirmation. A closing chapter covers AI video, voice and payment-verification habits. Interactive browser training built around one essential skill.
Bad News Game
A browser game from Cambridge University's Social Decision-Making Lab where you win by running a fake-news operation: impersonation, conspiracy, polarization and emotional manipulation. Playing the attacker teaches how disinformation actually spreads, and studies show it reduces belief in false claims afterward. Aimed at teens and adults; each round takes about fifteen minutes. Free, research-validated inoculation tool.
Harmony Square
A companion game to Bad News set in a small town square: players learn political disinformation tactics by deploying them, from false experts to exploiting outrage. The result is psychological inoculation against manipulation, with peer-reviewed evidence behind it. Aimed at teens, adults and civic-education classrooms. Free, playable in the browser in one sitting.
RumorGuard
The News Literacy Project's RumorGuard breaks down real viral claims with a repeatable five-factor evaluation: evidence, source, context, reasoning and authenticity. Each case study shows the claim, the checks run, and the verdict. Built for students and news consumers who want to watch verification happen on real content. Free, updated continuously with new viral cases.
A Survey on Hallucination in Large Language Models
The most-cited survey of hallucination in large language models, laying out its taxonomy: factual errors, math and reasoning errors, fake citations, and instruction-following failures, alongside the mechanisms behind them. You learn to name the shape of a wrong answer before checking it, turning the verification checklist from a ritual into a targeted scan. A widely referenced research survey mapping challenges and open questions. Free preprint by a large international team.
Chain-of-Verification Reduces Hallucination in Large Language Models
The research paper that formalizes asking a model to check its own work - and measures exactly how far that gets you. It introduces Chain-of-Verification, where the model drafts, generates verification questions, answers them independently, then revises, and reports where self-checking still leaves confident errors intact. Essential reading for why model self-grading is necessary but never sufficient. Published at ACL Findings 2024 with a free preprint and released code.
GPT detectors are biased against non-native English writers
The Stanford study showing that AI-text detectors misclassify non-native English writing as machine-generated at high rates, while simple paraphrasing defeats detectors regardless. It is the empirical case that detector-based policing of AI use is the wrong skill: the signal is unreliable and the incentives it creates are perverse. Learn why disclosure and verification, not detector evasion, are the defensible professional stance. Free preprint of a peer-reviewed Patterns article.
AI slop
Wikipedia's encyclopedic treatment of AI slop - the flood of low-quality, mass-generated AI content - covering its forms, causes, detection, and impact on search and social platforms. You study a maintained taxonomy of what slop looks like across text, images and video, plus the vocabulary to name what you are seeing at a glance. Heavily referenced with news and research citations that lead to deeper reading. A living article, continuously updated as the phenomenon evolves.
Wikipedia: Reliable Sources
Wikipedia's own policy page on source reliability: the rules that decide what counts as evidence on Wikipedia, how secondary and primary sources are weighed, and how fringe claims are handled. Studying it reveals the machinery behind the encyclopedia's reliability judgments. Aimed at readers who want to know when to trust a Wikipedia article and how to check its edit history. Free, community-maintained policy documentation.
